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Yayın Energy and data cooperative multiple access channel with intermittent data arrivals(IEEE, 2018-03) Gürakan, Berk; Kaya, Onur; Ulukuş, ŞennurWe consider an energy harvesting two user cooperative Gaussian multiple access channel, where both of the users harvest energy from nature. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. We study two scenarios within this model. In the first scenario, the data packets arrive intermittently over time. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. We first show that there exists an optimal policy, in which the single user rate constraints in each time slot are tight, yielding a one-to-one relation between the powers and rates. Then, we formulate the departure region maximization problem as a weighted sum departure maximization in terms of rates only. Next, we propose a sequential convex approximation method to approximate the problem at each step and show that it converges to the optimal solution. We solve the approximate problems using an inner-outer decomposition method. In the second scenario, the data packets are available at the beginning of the transmission, but the users now have the ability to cooperate at the battery level (energy cooperation), in addition to data cooperation. The energy cooperation is facilitated by wireless energy transfer and is bidirectional. For this scenario, we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region. We provide necessary conditions for energy transfer and prove some properties of the optimal transmit policy, thereby shedding some light on the interplay between energy and data cooperation.Yayın FSRFT - Fast simplified real frequency technique via selective target data approach for broadband double matching(IEEE, 2017-02) Köprü, RamazanThis brief introduces a broadband double-matching (DM) solver called fast simplified real frequency technique (FSRFT). FSRFT is essentially a greatly accelerated variant of the well-known classical simplified real frequency technique (SRFT). The basic idea that turns the classical SRFT into a 'fast' SRFT relies on two main approaches: the selective target data approach (STDA) and the constraint optimization approach (COA). STDA constructs an optimization target data set formed of only critically selected target data whose element number is equal to or slightly greater than the order of the system unknowns n plus 1, {n}+1. In order to exhibit speed performance comparison between SRFT and FSRFT, an example design is considered. An exemplary DM problem, dealing with an {n}=6th order low-pass Chebyshev-type equalizer design to match the given generator and load impedances, has been solved by SRFT within 29 s using 90 target data in a typical computer - e.g., Intel 2.20-GHz i7 CPU with 8-GB RAM. On the other hand, the same problem has been solved by the newly proposed FSRFT within only 0.6 s using only n+1=7 critically selected target data in the same computer. FSRFT introduced herein works in any domain, i.e., lumped, distributed, and mixed.Yayın Investigation of symptom-specific functional connectivity patterns in Parkinson’s disease(Springer-Verlag Italia S.R.L., 2025-06-14) Kıçik, Ani; Bayram, Ali; Erdoğdu, Emel; Kurt, Elif; Sarıdede, Dilek Betül; Cengiz, Sevim; Bilgiç, Başar; Hanağası, Haşmet; Öztürk Işık, Esin; Gürvit, Hakan; Tüzün, Erdem; Demiralp, TamerParkinson’s disease (PD) is a complex neurodegenerative disease, characterized by pronounced heterogeneity in symptoms. This study investigates the functional connectivity (FC) patterns associated with distinct symptom clusters, aiming to elucidate the heterogeneity in PD and uncover the neural mechanisms underlying its motor and cognitive symptoms. Resting-state functional MRI (rs-fMRI) data from 55 non-demented PD patients and 24 healthy controls (HC) were used to perform seed-to-seed FC analyses. A clustering algorithm was applied to the cognitive and motor scores of all PD patients to generate relatively homogeneous symptomatic subgroups. PD patients exhibited a general decrease in FC within a network comprising the sensorimotor network (SMN) and the visual network (VN) regions. Symptom-based clustering revealed three relatively homogeneous subgroups, exhibiting a gradient pattern: patients with greater motor deficits showed significant disconnection within the SMN, whereas patients with greater visuospatial deficits exhibited reduced FC in an extended subnetwork, with pronounced disconnections between the VN and SMN areas. Our study demonstrated a notable disconnection between the SMN and VN, indicating impaired visual-motor integration in PD. Stronger disconnection within the SMN was associated with greater motor dysfunction, and stronger visual-sensorimotor disconnections were associated with greater visuospatial deficits. These findings suggest that at least two separate routes of functional disconnection may be responsible for the inhomogeneous symptom distribution in PD.
